network_dense.py 文件源码

def _create_optimizer(self,
                          loss: tf.Tensor,
                          learning_rate: Union[tf.Tensor, float],
                          momentum: Union[tf.Tensor, float],
                          threshold: float) -> tf.Operation:

        if threshold is not None:
            return self._create_optimizer_sparse(loss=loss,
                                                 threshold=threshold,
                                                 learning_rate=learning_rate,
                                                 momentum=momentum)
        with tf.variable_scope('optimizer'):

            optimizer = tf.train.MomentumOptimizer(learning_rate=learning_rate,
                                                   momentum=momentum,
                                                   name='optimizer')
            self.global_step = tf.Variable(0)
            train_op = optimizer.minimize(loss,
                                          global_step=self.global_step,
                                          name='train_op')

            return train_op